class_docstr: ARLSTem stemmer : a light Arabic Stemming algorithm without any dictionary.
  Department of Telecommunication & Information Processing. USTHB University,
  Algiers, Algeria.
  ARLSTem.stem(token) returns the Arabic stem for the input token.
  The ARLSTem Stemmer requires that all tokens are encoded using Unicode
  encoding.
class_docstr_tok: ["ARLSTem","stemmer",":","a","light","Arabic","Stemming","algorithm","without","any","dictionary",".","Department","of","Telecommunication","&","Information","Processing",".","USTHB","University",",","Algiers",",","Algeria",".","ARLSTem.stem","(","token",")","returns","the","Arabic","stem","for","the","input","token",".","The","ARLSTem","Stemmer","requires","that","all","tokens","are","encoded","using","Unicode","encoding","."]
docstr: stem the future prefixes
docstr_tok: ["stem","the","future","prefixes"]
code: def verb_t5(self, token):
      """
      stem the future prefixes
      """
      if len(token) > 4:
          for pr2 in self.verb_pr22:
              if token.startswith(pr2):
                  return token[2:]
          for pr2 in self.verb_pr2:
              if token.startswith(pr2):
                  return token[2:]
      return token
  
file_path: nltk/nltk/stem/arlstem.py
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 13 for calling the ARLSTem obj's underlying member method code with example usage: obj.verb_t5(token) and returns: token, token, token